fastdtw

Last update: 18/05/2026

fastdtw

A Python implementation of FastDTW

Latest version: 0.3.4

Maintenance score

Safety score

Popularity score

This project has been inactive for more than one year

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Security

	Vulnerabilities
Version	Suggest	Low	Medium	High	Critical

0.3.4	0	0	0	0	0
0.3.2	0	0	0	0	0
0.3.1	0	0	0	0	0
0.3.0	0	0	0	0	0
0.2.2	0	0	0	0	0
0.2.1	0	0	0	0	0
0.2.0	0	0	0	0	0
0.1.0	0	0	0	0	0

Stability

Latest release:

0.3.4 - This version may not be safe as it has not been updated for a long time. Find out if your coding project uses this component and get notified of any reported security vulnerabilities with Meterian-X Open Source Security Platform

Licensing

Maintain your licence declarations and avoid unwanted licences to protect your IP the way you intended.

MIT - MIT License

Not a wildcard

Not proprietary

OSI Compliant

fastdtw

Python implementation of FastDTW <http://cs.fit.edu/~pkc/papers/tdm04.pdf>_ [1]_, which is an approximate Dynamic Time Warping (DTW) algorithm that provides optimal or near-optimal alignments with an O(N) time and memory complexity.

Install

pip install fastdtw

Example

import numpy as np from scipy.spatial.distance import euclidean

from fastdtw import fastdtw

x = np.array([[1,1], [2,2], [3,3], [4,4], [5,5]]) y = np.array([[2,2], [3,3], [4,4]]) distance, path = fastdtw(x, y, dist=euclidean) print(distance)

References

.. [1] Stan Salvador, and Philip Chan. "FastDTW: Toward accurate dynamic time warping in linear time and space." Intelligent Data Analysis 11.5 (2007): 561-580.